Title :
Hellinger Versus Kullback–Leibler Multivariable Spectrum Approximation
Author :
Ferrante, Augusto ; Pavon, Michele ; Ramponi, Federico
Author_Institution :
Dipt. di Ingegne- ria dell´´Inf., Univ. di Padova, Padova
fDate :
5/1/2008 12:00:00 AM
Abstract :
In this paper, we study a matricial version of a generalized moment problem with degree constraint. We introduce a new metric on multivariable spectral densities induced by the family of their spectral factors, which, in the scalar case, reduces to the Hellinger distance. We solve the corresponding constrained optimization problem via duality theory. A highly nontrivial existence theorem for the dual problem is established in the Byrnes-Lindquist spirit. A matricial Newton-type algorithm is finally provided for the numerical solution of the dual problem. Simulation indicates that the algorithm performs effectively and reliably.
Keywords :
Newton method; approximation theory; matrix algebra; optimisation; Byrnes-Lindquist spirit; Hellinger distance; Kullback-Leibler multivariable spectrum approximation; constrained optimization problem; duality theory; generalized moment problem; matricial Newton-type algorithm; multivariable spectral densities; Collaborative work; Constraint optimization; Constraint theory; Entropy; Filters; Interpolation; Multidimensional systems; Optimization methods; Robust control; Signal processing algorithms; Approximation of multivariable power spectra; Hellinger distance; Kullback–Leibler index; convex optimization; matricial descent method;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2008.920238